Muhannad Quwaider | Jordan University of Science and Technology (original) (raw)

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Papers by Muhannad Quwaider

Research paper thumbnail of Network-integrated sensing and energy-aware protocols in wireless body area networks

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Research paper thumbnail of Cross-Lingual Short-Text Document Classification for Facebook Comments

2014 International Conference on Future Internet of Things and Cloud, 2014

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Research paper thumbnail of 2014 5th International Conference on Information and Communication Systems (ICICS)

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Research paper thumbnail of Text-independent Speaker Recognition using Deep Neural Networks

2021 International Conference on Information Technology (ICIT)

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Research paper thumbnail of A Deep Learning Framework for Automatic Detection of Hate Speech Embedded in Arabic Tweets

Arabian Journal for Science and Engineering

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Research paper thumbnail of Performance Evaluation and Enhancement of VLAN via Wireless Networks using OPNET Modeler

International Journal of Wireless & Mobile Networks

A VLAN is a logical connection that allows hosts to be grouped together in the same broadcast dom... more A VLAN is a logical connection that allows hosts to be grouped together in the same broadcast domain, so that packets are delivered only to ports that are combined to the same VLAN. We can improve wireless network performance and save bandwidth through the characteristic VLAN network. In addition, the implementation of VLAN greatly improves wireless network security by reducing the number of hosts receiving copies of frames broadcast by switches, thus keeping hosts holding critical data on a separate VLAN. In this paper we compare wireless network with VLAN via wireless network. The proposed network is evaluated within terms of delay and average throughput using web browsing applications and file transfer in heavy traffic. The simulation was carried out using OPNET 14.5 modeler and the results show that the use of VLAN via wireless network improved performance by reducing traffic resulting in a minimized delay time. Furthermore, VLAN implementation reduces network throughput because the traffic received and transmitted has a positive relationship with throughput. Eventually, we investigated the use of adhoc routing protocols such as AODV, DSR, OLSR, TORA and GPR to improve the performance of wireless VLAN networks.

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Research paper thumbnail of Congestion Control Model for Securing Internet of Things Data Flow

Ad Hoc Networks

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Research paper thumbnail of The Impact of Video Games on the Players Behaviors: A Survey

Procedia Computer Science

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Research paper thumbnail of Neural Network Model as Internet of Things Congestion Control using PID Controller and Immune-Hill-Climbing Algorithm

Simulation Modelling Practice and Theory

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Research paper thumbnail of Multi-tier cloud infrastructure support for reliable global health awareness system

Simulation Modelling Practice and Theory

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Research paper thumbnail of IoT Privacy and Security: Challenges and Solutions

Applied Sciences

Privacy and security are among the significant challenges of the Internet of Things (IoT). Improp... more Privacy and security are among the significant challenges of the Internet of Things (IoT). Improper device updates, lack of efficient and robust security protocols, user unawareness, and famous active device monitoring are among the challenges that IoT is facing. In this work, we are exploring the background of IoT systems and security measures, and identifying (a) different security and privacy issues, (b) approaches used to secure the components of IoT-based environments and systems, (c) existing security solutions, and (d) the best privacy models necessary and suitable for different layers of IoT driven applications. In this work, we proposed a new IoT layered model: generic and stretched with the privacy and security components and layers identification. The proposed cloud/edge supported IoT system is implemented and evaluated. The lower layer represented by the IoT nodes generated from the Amazon Web Service (AWS) as Virtual Machines. The middle layer (edge) implemented as a Ra...

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Research paper thumbnail of Cloudlet-based for big data collection in body area networks

2013 IEEE Third International Conference on Information Science and Technology (ICIST), 2013

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Research paper thumbnail of Cloudlet-based Efficient Data Collection in Wireless Body Area Networks

Simulation Modelling Practice and Theory, 2015

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Research paper thumbnail of An efficient big data collection in Body Area Networks

2014 5th International Conference on Information and Communication Systems (ICICS), 2014

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Research paper thumbnail of Human Annotated Arabic Dataset of Book Reviews for Aspect Based Sentiment Analysis

2015 3rd International Conference on Future Internet of Things and Cloud, 2015

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Research paper thumbnail of Physical Context Detection using Wearable Wireless Sensor Networks

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Research paper thumbnail of Smart Community Health Awareness Model

In this paper we present a novel cloud supported model for efficient community health awareness i... more In this paper we present a novel cloud supported model for efficient community health awareness in presence of a large scale WBANs data generation. The objective is to process this big data in order to detect the abnormal data using MapReduce infrastructure and user defined functions with minimum processing delay. The goal is to have a large monitored data of WBANs to be available to the end user or to the decision maker in reliable manner. The proposed work is minimizing the data processing delay by choosing cloudlet or local cloud model and MapReduce infrastructure. So, the overall delay is minimized, thus leading to detect the abnormal data in the cloud in real time mode. Performance results show that integrating the MapReduce capabilities with cloud computing model will significantly reduce the processing delay.

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Research paper thumbnail of Cloud-assisted Data Management in Wireless Body Area Networks

International Journal of Computational Science and Engineering

This paper presents an efficient large scale data collection in Wireless Body Area Network (WBANs... more This paper presents an efficient large scale data collection in Wireless Body Area Network (WBANs) in the presence of cloudlet-based prototype system. The key contribution of this paper is to collect the observed data of WBANs in a large scale and convey it in consistent manner to the other end of service providers. A model of WBANs is proposed in this work including virtualized machines and Cloudlet in order to characterize the efficient WBANs data collection. A scalable storage and processing infrastructure have been proposed to support large scale WBANs system, which is efficiently capable to handle the big data generated by large number of WBANs users. The proposed model supports effective cost communication technologies through Wi-Fi technology. Performance results of the proposed prototype are evaluated using advanced CloudSim simulator. The performance results show that the consumed power and packet delay of the collected data is decreased by increasing the number virtualized...

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Research paper thumbnail of A cloud supported model for efficient community health awareness

Pervasive and Mobile Computing, 2015

ABSTRACT The needs for efficient and scalable community health awareness model become a crucial i... more ABSTRACT The needs for efficient and scalable community health awareness model become a crucial issue in today’s health care applications. Many health care service providers need to provide their services for long terms, in real time and interactively. Many of these applications are based on the emerging Wireless Body Area networks (WBANs) technology. WBANs have developed as an effective solution for a wide range of healthcare, military, sports, general health and social applications. On the other hand, handling data in a large scale (currently known as Big Data) requires an efficient collection and processing model with scalable computing and storage capacity. Therefore, a new computing paradigm is needed such as Cloud Computing and Internet of Things (IoT). In this paper we present a novel cloud supported model for efficient community health awareness in presence of a large scale WBANs data generation. The objective is to process this big data in order to detect the abnormal data using MapReduce infrastructure and user defined functions with minimum processing delay. The goal is to have a large monitored data of WBANs to be available to the end user or to the decision maker in reliable manner. While reducing data packet processing energy, the proposed work is minimizing the data processing delay by choosing cloudlet or local cloud model and MapReduce infrastructure. So, the overall delay is minimized, thus leading to detect the abnormal data in the cloud in real time mode. In this paper we present a multi-layer computing model composed of Local Cloud (LC) layer and Enterprise Cloud (EP) layer that aim to process the collected data from Monitored Subjects (MSs) in a large scale to generate useful facts, observations or to find abnormal phenomena within the monitored data. Performance results show that integrating the MapReduce capabilities with cloud computing model will reduce the processing delay. The proposed MapReduce infrastructure has been also applied in lower layer, such as LC in order to reduce the amount of communications and processing delay. Performance results show that applying MapReduce infrastructure in lower tire will significantly decrease the overall processing delay.

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Research paper thumbnail of Experimental Framework for Mobile Cloud Computing System

Procedia Computer Science, 2015

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Research paper thumbnail of Network-integrated sensing and energy-aware protocols in wireless body area networks

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Research paper thumbnail of Cross-Lingual Short-Text Document Classification for Facebook Comments

2014 International Conference on Future Internet of Things and Cloud, 2014

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Research paper thumbnail of 2014 5th International Conference on Information and Communication Systems (ICICS)

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Research paper thumbnail of Text-independent Speaker Recognition using Deep Neural Networks

2021 International Conference on Information Technology (ICIT)

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Research paper thumbnail of A Deep Learning Framework for Automatic Detection of Hate Speech Embedded in Arabic Tweets

Arabian Journal for Science and Engineering

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Research paper thumbnail of Performance Evaluation and Enhancement of VLAN via Wireless Networks using OPNET Modeler

International Journal of Wireless & Mobile Networks

A VLAN is a logical connection that allows hosts to be grouped together in the same broadcast dom... more A VLAN is a logical connection that allows hosts to be grouped together in the same broadcast domain, so that packets are delivered only to ports that are combined to the same VLAN. We can improve wireless network performance and save bandwidth through the characteristic VLAN network. In addition, the implementation of VLAN greatly improves wireless network security by reducing the number of hosts receiving copies of frames broadcast by switches, thus keeping hosts holding critical data on a separate VLAN. In this paper we compare wireless network with VLAN via wireless network. The proposed network is evaluated within terms of delay and average throughput using web browsing applications and file transfer in heavy traffic. The simulation was carried out using OPNET 14.5 modeler and the results show that the use of VLAN via wireless network improved performance by reducing traffic resulting in a minimized delay time. Furthermore, VLAN implementation reduces network throughput because the traffic received and transmitted has a positive relationship with throughput. Eventually, we investigated the use of adhoc routing protocols such as AODV, DSR, OLSR, TORA and GPR to improve the performance of wireless VLAN networks.

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Research paper thumbnail of Congestion Control Model for Securing Internet of Things Data Flow

Ad Hoc Networks

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Research paper thumbnail of The Impact of Video Games on the Players Behaviors: A Survey

Procedia Computer Science

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Research paper thumbnail of Neural Network Model as Internet of Things Congestion Control using PID Controller and Immune-Hill-Climbing Algorithm

Simulation Modelling Practice and Theory

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Multi-tier cloud infrastructure support for reliable global health awareness system

Simulation Modelling Practice and Theory

Bookmarks Related papers MentionsView impact

Research paper thumbnail of IoT Privacy and Security: Challenges and Solutions

Applied Sciences

Privacy and security are among the significant challenges of the Internet of Things (IoT). Improp... more Privacy and security are among the significant challenges of the Internet of Things (IoT). Improper device updates, lack of efficient and robust security protocols, user unawareness, and famous active device monitoring are among the challenges that IoT is facing. In this work, we are exploring the background of IoT systems and security measures, and identifying (a) different security and privacy issues, (b) approaches used to secure the components of IoT-based environments and systems, (c) existing security solutions, and (d) the best privacy models necessary and suitable for different layers of IoT driven applications. In this work, we proposed a new IoT layered model: generic and stretched with the privacy and security components and layers identification. The proposed cloud/edge supported IoT system is implemented and evaluated. The lower layer represented by the IoT nodes generated from the Amazon Web Service (AWS) as Virtual Machines. The middle layer (edge) implemented as a Ra...

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Cloudlet-based for big data collection in body area networks

2013 IEEE Third International Conference on Information Science and Technology (ICIST), 2013

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Cloudlet-based Efficient Data Collection in Wireless Body Area Networks

Simulation Modelling Practice and Theory, 2015

Bookmarks Related papers MentionsView impact

Research paper thumbnail of An efficient big data collection in Body Area Networks

2014 5th International Conference on Information and Communication Systems (ICICS), 2014

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Human Annotated Arabic Dataset of Book Reviews for Aspect Based Sentiment Analysis

2015 3rd International Conference on Future Internet of Things and Cloud, 2015

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Physical Context Detection using Wearable Wireless Sensor Networks

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Smart Community Health Awareness Model

In this paper we present a novel cloud supported model for efficient community health awareness i... more In this paper we present a novel cloud supported model for efficient community health awareness in presence of a large scale WBANs data generation. The objective is to process this big data in order to detect the abnormal data using MapReduce infrastructure and user defined functions with minimum processing delay. The goal is to have a large monitored data of WBANs to be available to the end user or to the decision maker in reliable manner. The proposed work is minimizing the data processing delay by choosing cloudlet or local cloud model and MapReduce infrastructure. So, the overall delay is minimized, thus leading to detect the abnormal data in the cloud in real time mode. Performance results show that integrating the MapReduce capabilities with cloud computing model will significantly reduce the processing delay.

Bookmarks Related papers MentionsView impact

Research paper thumbnail of Cloud-assisted Data Management in Wireless Body Area Networks

International Journal of Computational Science and Engineering

This paper presents an efficient large scale data collection in Wireless Body Area Network (WBANs... more This paper presents an efficient large scale data collection in Wireless Body Area Network (WBANs) in the presence of cloudlet-based prototype system. The key contribution of this paper is to collect the observed data of WBANs in a large scale and convey it in consistent manner to the other end of service providers. A model of WBANs is proposed in this work including virtualized machines and Cloudlet in order to characterize the efficient WBANs data collection. A scalable storage and processing infrastructure have been proposed to support large scale WBANs system, which is efficiently capable to handle the big data generated by large number of WBANs users. The proposed model supports effective cost communication technologies through Wi-Fi technology. Performance results of the proposed prototype are evaluated using advanced CloudSim simulator. The performance results show that the consumed power and packet delay of the collected data is decreased by increasing the number virtualized...

Bookmarks Related papers MentionsView impact

Research paper thumbnail of A cloud supported model for efficient community health awareness

Pervasive and Mobile Computing, 2015

ABSTRACT The needs for efficient and scalable community health awareness model become a crucial i... more ABSTRACT The needs for efficient and scalable community health awareness model become a crucial issue in today’s health care applications. Many health care service providers need to provide their services for long terms, in real time and interactively. Many of these applications are based on the emerging Wireless Body Area networks (WBANs) technology. WBANs have developed as an effective solution for a wide range of healthcare, military, sports, general health and social applications. On the other hand, handling data in a large scale (currently known as Big Data) requires an efficient collection and processing model with scalable computing and storage capacity. Therefore, a new computing paradigm is needed such as Cloud Computing and Internet of Things (IoT). In this paper we present a novel cloud supported model for efficient community health awareness in presence of a large scale WBANs data generation. The objective is to process this big data in order to detect the abnormal data using MapReduce infrastructure and user defined functions with minimum processing delay. The goal is to have a large monitored data of WBANs to be available to the end user or to the decision maker in reliable manner. While reducing data packet processing energy, the proposed work is minimizing the data processing delay by choosing cloudlet or local cloud model and MapReduce infrastructure. So, the overall delay is minimized, thus leading to detect the abnormal data in the cloud in real time mode. In this paper we present a multi-layer computing model composed of Local Cloud (LC) layer and Enterprise Cloud (EP) layer that aim to process the collected data from Monitored Subjects (MSs) in a large scale to generate useful facts, observations or to find abnormal phenomena within the monitored data. Performance results show that integrating the MapReduce capabilities with cloud computing model will reduce the processing delay. The proposed MapReduce infrastructure has been also applied in lower layer, such as LC in order to reduce the amount of communications and processing delay. Performance results show that applying MapReduce infrastructure in lower tire will significantly decrease the overall processing delay.

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Research paper thumbnail of Experimental Framework for Mobile Cloud Computing System

Procedia Computer Science, 2015

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